Highway traffic laws in most jurisdictions require vehicles to yield to emergency vehicles. However, the cabins of modern automobiles are well insulated from outside noise, and the use of sirens and their volume may be limited to prevent noise pollution. These and other factors may make it difficult for drivers to detect siren sounds produced by emergency vehicles. Also, semi or fully autonomous vehicles must be able to detect emergency vehicles to operate safely and within the law.
Sensing systems in automotive applications may use a variety of sensor types, but each is associated with drawbacks. Optical systems using cameras that capture images, or optical sensors to capture reflected light (lidar), are limited by “line-of-sight”, are relatively expensive, and require powerful processors to deal with large amounts of data. Radar systems that detect reflected radio waves are less data-intensive, but provide far less information. Systems that detect reflected ultrasound waves are useful only in short ranges, and are limited to applications such as parking-assist sensors.
Systems using audio sensors face challenges. First, such systems need to be sensitive enough to detect and discriminate faint noises at a distance, without being overwhelmed by loud noises at close distances. Second, detectable sounds vary significantly in different environments and operating conditions. For example, North American emergency vehicle sirens typically have a pitch that varies cyclically within a band of between about 500 Hz to about 2000 Hz, but the frequency range and cycle period still varies greatly between different sirens, while European sirens typically alternate between two discrete frequencies. Further, the perceived pitch of the siren may be significantly higher or lower as a result of the Doppler Effect caused by relative motion between the emergency vehicle and the sensing automobile.
There is a need in the art for an effective automotive audio detection system for detecting emergency vehicle sirens.